The paper presents a novel approach to solving problems involved in the application of a genetic algorithm to determine the optimal tyre pitch sequence to reduce the tyre air-pumping noise which is generated by the repeated compression and expansion of the air cavity between the tyre pitch and the road surface. The genetic algorithm was used to determine the optimal tyre pitch sequence with a low level of tyre air-pumping noise using the image-based air-pumping model. In the genetic algorithm used in previous studies, there are a number of problems related to the encoding structure and the selection of an objective function. This paper proposes a single encoding element with five integers, a divergent objective function based on an evolutionary process, and the optimal evolutionary rate based on the Shannon entropy in an attempt to solve the problems. The results of the proposed genetic algorithm with an evolutionary process are compared with those of a randomized algorithm. The randomized algorithm is a traditional method used to obtain the tyre pitch sequence. It was confirmed that the genetic algorithm more effectively reduces the peak value of the predicted tyre air-pumping noise. The consistency and cohesion of the obtained simulation results are also improved.

A magainin derivative, designated MSI-344, was produced in Escherichia coli as fusion protein, by utilizing a truncated amidophsphoribosyltransferase of E. coli as a fusion partner. Bacterial cells transformed with the gene encoding the fusion protein were grown to a high cell density and induced with isopropyl-1-thio-b-D-galatoside (IPTG) to initiate product expression. The fusion protein was accumulated into cytoplasmic inclusion body and recombinant MSI-344 was released from the fusion partner by hydroxylamine treatment. Following cleavage of the fusion protein with hydroxylamine, the released MSI-344 was purified to homogeneity by cationic exchange chromatography. The final purity was at least 95% by reversed-phase high performance liquid chromatography (RP-HPLC). Purified recombinant MSI-344 was found to be indistinguishable from the synthetic peptide determined by amino acid sequences and antimicrobial activity assay.

Many studies relating to vehicle door closure have focused on noise and vibration, and little attention has been given to the pressure rise or velocity distribution inside a cabin. Too high a pressure rise may, however, exert a resistive force when a car door closes and induce a mechanical reaction of the pars flaccida related to passenger comfort. Thus, this study investigates the effects of the angular velocity of the door and the body leakage on variations in the cabin flows. First, tests for the body leakage were performed for 43 vehicles. Then, three-dimensional numerical analyses with a dynamic mesh were performed and experiments were conducted to verify the results. It was found that the pressure rise is a strong function of the door's angular velocity and that the peak pressure increases almost linearly with increasing angular velocity. However, the body leakage has less effect on the pressure rise unless the extent of the leakage is significantly increased. The pressure rise that occurs while closing a cabin door could be greatly reduced by lowering the door's angular velocity or by developing a mechanism that can greatly increase the body leakage temporarily.

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The paper presents the novel approach to solve some problems occurred in application of the genetic algorithm to the determination of the optimal tire pattern sequence in order to reduce the tire air-pumping noise which is generated by the repeated compression and expansion of the air cavity between tire pattern and road surface. The genetic algorithm has been used to find the optimal tire pattern sequence having a low level of tire air-pumping noise using the image based air-pumping model. In the genetic algorithm used in the previous researches, there are some problems in the encoding structure and the selection of objective function. The paper proposed single encoding element with five integers, divergent objective function based on evolutionary process and the optimal evolutionary rate based on Shannon entropy to solve the problems. The results of the proposed genetic algorithm with evolutionary process are compared with those of the randomized algorithm without evolutionary process on the two-dimensional normal distribution. It is confirmed that the genetic algorithm is more effective to reduce the peak value of the predicted tire air-pumping noise and the consistency and cohesion of the obtained simulation results are also improved in terms of probability. .